Customer Churn Predictor Web App
Maaz Ahmad
This app leverages machine learning to help businesses identify which customers are likely to leave, allowing them to take proactive steps to retain them. 🛡️
You can try the app yourself here:
🔍 Key Features:
- User-Friendly Interface: Built with Streamlit for easy interaction.
- Accurate Predictions: Utilises a random forest classifier model pipeline trained on historical customer data, achieving a 96% F1-score.
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🔧 Tech Stack:
- Python to make the app and implementing the model
- Jupyter notebook for loading, cleaning, and analysing the dataset
- Pandas for data cleaning and preprocessing
- Scikit-learn for training and evaluating the models
- Streamlit for the app interface
To take a look at the Jupyter notebook and other related files, you can visit this GitHub repository:
Dataset used from Kaggle:
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Posted Jul 11, 2024
Streamlit web app with an integrated classifier model trained on dataset, from a customer info bank dataset, after cleaning and preprocessing the data.
